993 resultados para Markov process


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Ground-penetrating radar (GPR) has the potential to provide valuable information on hydrological properties of the vadose zone because of their strong sensitivity to soil water content. In particular, recent evidence has suggested that the stochastic inversion of crosshole GPR data within a coupled geophysical-hydrological framework may allow for effective estimation of subsurface van-Genuchten-Mualem (VGM) parameters and their corresponding uncertainties. An important and still unresolved issue, however, is how to best integrate GPR data into a stochastic inversion in order to estimate the VGM parameters and their uncertainties, thus improving hydrological predictions. Recognizing the importance of this issue, the aim of the research presented in this thesis was to first introduce a fully Bayesian inversion called Markov-chain-Monte-carlo (MCMC) strategy to perform the stochastic inversion of steady-state GPR data to estimate the VGM parameters and their uncertainties. Within this study, the choice of the prior parameter probability distributions from which potential model configurations are drawn and tested against observed data was also investigated. Analysis of both synthetic and field data collected at the Eggborough (UK) site indicates that the geophysical data alone contain valuable information regarding the VGM parameters. However, significantly better results are obtained when these data are combined with a realistic, informative prior. A subsequent study explore in detail the dynamic infiltration case, specifically to what extent time-lapse ZOP GPR data, collected during a forced infiltration experiment at the Arrenaes field site (Denmark), can help to quantify VGM parameters and their uncertainties using the MCMC inversion strategy. The findings indicate that the stochastic inversion of time-lapse GPR data does indeed allow for a substantial refinement in the inferred posterior VGM parameter distributions. In turn, this significantly improves knowledge of the hydraulic properties, which are required to predict hydraulic behaviour. Finally, another aspect that needed to be addressed involved the comparison of time-lapse GPR data collected under different infiltration conditions (i.e., natural loading and forced infiltration conditions) to estimate the VGM parameters using the MCMC inversion strategy. The results show that for the synthetic example, considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions. When investigating data collected at the Arrenaes field site, further complications arised due to model error and showed the importance of also including a rigorous analysis of the propagation of model error with time and depth when considering time-lapse data. Although the efforts in this thesis were focused on GPR data, the corresponding findings are likely to have general applicability to other types of geophysical data and field environments. Moreover, the obtained results allow to have confidence for future developments in integration of geophysical data with stochastic inversions to improve the characterization of the unsaturated zone but also reveal important issues linked with stochastic inversions, namely model errors, that should definitely be addressed in future research.

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This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

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ISSUE: This article explores mechanisms of the efficacy of brief intervention (BI). APPROACH: We conducted a BI trial at the emergency department of the Lausanne University Hospital, of whom 987 at-risk drinkers were randomised into BI and control groups. The overall results demonstrated a general decrease in alcohol use with no differences across groups. The intention to change was explored among 367 patients who completed BI. Analyses of 97 consecutive tape-recorded sessions explored patient and counsellor talks during BI, and their relationship to alcohol use outcome. KEY FINDINGS: Evaluation of the articulation between counsellor behaviours and patient language revealed a robust relationship between counsellor motivational interviewing (MI) skills and patient change talk during the intervention. Further exploration suggested that communication characteristics of patients during BI predicted changes in alcohol consumption 12 months later. Moreover, despite systematic training, important differences in counsellor performance were highlighted. Counsellors who had superior MI skills achieved better outcomes overall, and maintained efficacy across all levels of patient ability to change, whereas counsellors with inferior MI skills were effective mostly with patients who had higher levels of ability to change. Finally, the descriptions of change talk trajectories within BI and their association with drinking 12 months later showed that final states differed from initial states, suggesting an impact resulting from the progression of change talk during the course of the intervention. IMPLICATION: These findings suggest that BI should focus on the general MI attitude of counsellors who are capable of eliciting beneficial change talk from patients. [Daeppen J-B, Bertholet N, Gaume J. What process research tells us about brief intervention efficacy.

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OBJECTIVE: Routine prenatal screening for Down syndrome challenges professional non-directiveness and patient autonomy in daily clinical practices. This paper aims to describe how professionals negotiate their role when a pregnant woman asks them to become involved in the decision-making process implied by screening. METHODS: Forty-one semi-structured interviews were conducted with gynaecologists-obstetricians (n=26) and midwives (n=15) in a large Swiss city. RESULTS: Three professional profiles were constructed along a continuum that defines the relative distance or proximity towards patients' demands for professional involvement in the decision-making process. The first profile insists on enforcing patient responsibility, wherein the healthcare provider avoids any form of professional participation. A second profile defends the idea of a shared decision making between patients and professionals. The third highlights the intervening factors that justify professionals' involvement in decisions. CONCLUSIONS: These results illustrate various applications of the principle of autonomy and highlight the complexity of the doctor-patient relationship amidst medical decisions today.

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The recommended dietary allowances of many expert committees (UK DHSS 1979, FAO/WHO/UNU 1985, USA NRC 1989) have set out the extra energy requirements necessary to support lactation on the basis of an efficiency of 80 per cent for human milk production. The metabolic efficiency of milk synthesis can be derived from the measurements of resting energy expenditure in lactating women and in a matched control group of non-pregnant non-lactating women. The results of the present study in Gambian women, as well as a review of human studies on energy expenditure during lactation performed in different countries, suggest an efficiency of human milk synthesis greater than the value currently used by expert committees. We propose that an average figure of 95 per cent would be more appropriate to calculate the energy cost of human lactation.

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This paper analyzes and evaluates, in the context of Ontology learning, some techniques to identify and extract candidate terms to classes of a taxonomy. Besides, this work points out some inconsistencies that may be occurring in the preprocessing of text corpus, and proposes techniques to obtain good terms candidate to classes of a taxonomy.

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Report by Iowa Department of Transportation about pavements materials.

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Collage is a pattern-based visual design authoring tool for the creation of collaborative learning scripts computationally modelled with IMS Learning Design (LD). The pattern-based visual approach aims to provide teachers with design ideas that are based on broadly accepted practices. Besides, it seeks hiding the LD notation so that teachers can easily create their own designs. The use of visual representations supports both the understanding of the design ideas and the usability of the authoring tool. This paper presents a multicase study comprising three different cases that evaluate the approach from different perspectives. The first case includes workshops where teachers use Collage. A second case implies the design of a scenario proposed by a third-party using related approaches. The third case analyzes a situation where students follow a design created with Collage. The cross-case analysis provides a global understanding of the possibilities and limitations of the pattern-based visual design approach.